Characterization of Chinese vinegars by electronic nose
Characterization of Chinese vinegars by electronic nose
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DOI：
10.1016/j.snb.2006.01.007
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发表时间：
2006-12
影响因子：
8.4
通讯作者：
Qinyi Zhang;Shunping Zhang;C. Xie;D. Zeng;C. Fan;Dengfeng Li;Z. Bai
中科院分区：
文献类型：
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作者：
Qinyi Zhang;Shunping Zhang;C. Xie;D. Zeng;C. Fan;Dengfeng Li;Z. Bai
本文采用含有 9 个纳米 ZnO 厚膜气体传感器的电子鼻对 17 种市售醋、乙酸和 5% 稀乙酸进行了分析，这些气体传感器分别掺杂 5wt.% 和 10wt.% TiO2、5 和 10wt.% MnO2、1wt.% V2O5、5wt.% Bi2O3、0.6 和 2.4wt.% Ag 和 5wt.% 分别为W。采用主成分分析（PCA）和聚类分析（CA）来调查样本群体中类别的存在。结果表明，电子鼻对食醋的表征与食醋的种类、原料、总酸度、发酵方法和产地高度相关，且这些影响因素并不是独立的。 CA结果表明，在电子鼻分析醋时，类型和发酵方法比其他影响因素更有效。最后，电子鼻收集的数据被应用到学习矢量量化（LVQ）神经网络中，起到对醋的识别和分类的作用。根据类型、原料、总酸度、发酵方法和产地，预测测试醋测量值的准确度分别为 72.1%、76.5%、77.9%、94.1% 和 82.4%。这项工作是建立醋气敏指纹数据库和开发用于醋质量控制的商用电子鼻的第一步。
In this paper, 17 commercial Chinese vinegars, acetic acid and 5% diluted acetic acid were analyzed by an electronic nose containing nine nano ZnO thick film gas sensors, which are doped by 5wt.% and 10wt.% TiO2, 5 and 10wt.% MnO2, 1wt.% V2O5, 5wt.% Bi2O3, 0.6 and 2.4wt.% Ag, and 5wt.% W, respectively. Principal component analysis (PCA) and cluster analysis (CA) were employed to investigate the presence of classes inside the sample population. It was shown that characterizing the Chinese vinegars by the electronic nose was highly related to their type, raw materials, total acidity, fermentation method and production area and all these influencing factors were not independent. The CA results indicated that the type and fermentation method were more effective than the other influencing factors when the vinegars were analyzed by the electronic nose. Finally, the data colleted by the electronic nose were applied to the learning vector quantization (LVQ) neural network performing the role of recognition and classification of the vinegars. The accuracy in terms of predicting tested vinegar measurements was 72.1%, 76.5%, 77.9%, 94.1% and 82.4% according to their type, raw materials, total acidity, fermentation method and production area, respectively. This work was the first step to establish a gas-sensing fingerprint database of Chinese vinegars and develop a commercial electronic nose on the Chinese vinegars quality control.